#include <itkConfidenceConnectedImageFilter.h>

Inheritance diagram for itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >:

Collaboration diagram for itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef InputImageType::IndexType	IndexType
typedef InputImageType::PixelType	InputImagePixelType
typedef InputImageType::Pointer	InputImagePointer
typedef InputImageType::RegionType	InputImageRegionType
typedef TInputImage	InputImageType
typedef NumericTraits < InputImagePixelType > ::RealType	InputRealType
typedef OutputImageType::PixelType	OutputImagePixelType
typedef OutputImageType::Pointer	OutputImagePointer
typedef OutputImageType::RegionType	OutputImageRegionType
typedef TOutputImage	OutputImageType
typedef SmartPointer< Self >	Pointer
typedef std::vector< IndexType >	SeedsContainerType
typedef ConfidenceConnectedImageFilter	Self
typedef InputImageType::SizeType	SizeType
typedef ImageToImageFilter < TInputImage, TOutputImage >	Superclass
Public Member Functions
void	AddSeed (const IndexType &seed)
void	ClearSeeds ()
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual const InputRealType &	GetMean ()
virtual const char *	GetNameOfClass () const
virtual const SeedsContainerType &	GetSeeds () const
virtual const InputRealType &	GetVariance ()
void	PrintSelf (std::ostream &os, Indent indent) const
void	SetSeed (const IndexType &seed)
	typedef (Concept::HasNumericTraits< InputImagePixelType >) InputHasNumericTraitsCheck
	typedef (Concept::HasNumericTraits< OutputImagePixelType >) OutputHasNumericTraitsCheck

virtual void	SetMultiplier (double _arg)
virtual double	GetMultiplier () const

virtual void	SetNumberOfIterations (unsigned int _arg)
virtual unsigned int	GetNumberOfIterations () const

virtual void	SetReplaceValue (OutputImagePixelType _arg)
virtual OutputImagePixelType	GetReplaceValue () const

virtual void	SetInitialNeighborhoodRadius (unsigned int _arg)
virtual const unsigned int &	GetInitialNeighborhoodRadius ()
Static Public Member Functions
static Pointer	New ()
Protected Member Functions
	ConfidenceConnectedImageFilter ()
void	EnlargeOutputRequestedRegion (DataObject *output)
void	GenerateData ()
void	GenerateInputRequestedRegion ()
	~ConfidenceConnectedImageFilter ()
Private Member Functions
	ConfidenceConnectedImageFilter (const Self &)
void	operator= (const Self &)
Private Attributes
unsigned int	m_InitialNeighborhoodRadius
InputRealType	m_Mean
double	m_Multiplier
unsigned int	m_NumberOfIterations
OutputImagePixelType	m_ReplaceValue
SeedsContainerType	m_Seeds
InputRealType	m_Variance

Detailed Description

template<class TInputImage, class TOutputImage>
class itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >

Segment pixels with similar statistics using connectivity.

This filter extracts a connected set of pixels whose pixel intensities are consistent with the pixel statistics of a seed point. The mean and variance across a neighborhood (8-connected, 26-connected, etc.) are calculated for a seed point. Then pixels connected to this seed point whose values are within the confidence interval for the seed point are grouped. The width of the confidence interval is controlled by the "Multiplier" variable (the confidence interval is the mean plus or minus the "Multiplier" times the standard deviation). If the intensity variations across a segment were gaussian, a "Multiplier" setting of 2.5 would define a confidence interval wide enough to capture 99% of samples in the segment.

After this initial segmentation is calculated, the mean and variance are re-calculated. All the pixels in the previous segmentation are used to calculate the mean the standard deviation (as opposed to using the pixels in the neighborhood of the seed point). The segmentation is then recalculated using these refined estimates for the mean and variance of the pixel values. This process is repeated for the specified number of iterations. Setting the "NumberOfIterations" to zero stops the algorithm after the initial segmentation from the seed point.

NOTE: the lower and upper threshold are restricted to lie within the valid numeric limits of the input data pixel type. Also, the limits may be adjusted to contain the seed point's intensity.

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Segment pixels with similar statistics using connectivity

Definition at line 63 of file itkConfidenceConnectedImageFilter.h.